Kai Zhang 
Performance Assessment for Process Monitoring and Fault Detection Methods 

Support

The objective of Kai Zhang and his research is to assess the existing process monitoring and fault detection (PM-FD) methods. His aim is to provide suggestions and guidance for choosing appropriate PM-FD methods, because the performance assessment study for PM-FD methods has become an area of interest in both academics and industry. The author first compares basic FD statistics, and then assesses different PM-FD methods to monitor the key performance indicators of static processes, steady-state dynamic processes and general dynamic processes including transient states. He validates the theoretical developments using both benchmark and real industrial processes.

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Table des matières

Assessing the performance of T2 and Q fault detection statistics.- Proposing a new performance evaluation index called expected detection delay (EDD).- Assessing the performance of different PM-FD methods using EDD when applied to detecting different types of faults.- Assessing the state-space-based PM-FD methods when applied to a real hot strip mill process.

A propos de l’auteur

Kai Zhang has just finished his Ph D defense. His research area covers multivariate statistical process monitoring (PM) methods, data-driven fault detection (FD) methods and performance evaluation for PM-FD methods.
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Langue Anglais ● Format PDF ● Pages 153 ● ISBN 9783658159719 ● Taille du fichier 2.8 MB ● Maison d’édition Springer Fachmedien Wiesbaden ● Lieu Wiesbaden ● Pays DE ● Publié 2016 ● Téléchargeable 24 mois ● Devise EUR ● ID 4984136 ● Protection contre la copie DRM sociale

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